Why Robots Won't Rule

Chris Malcolm, old enough to remember when one used chads to patch
binary programs, is a lecturer in the School of Artificial Intelligence of
the Division of Informatics of Edinburgh University. His research
interests include robot control architectures and the philosophy of
robotics.

click on image to enlarge. Graph by courtesy of Hans
Moravec.

There is a currently popular argument that within a few to several
decades robots (or some other kind of intelligent machine) will have
become so much more intelligent than us that they will take over the
world. This argument is seriously put forward by knowledgeable
scientists working in appropriate disciplines. They take different
attitudes to this future. For example, Professor Moravec (a roboticist
from Carnegie Mellon University, US) thinks this will be good, because
we will be handing the torch of future civilisation over to our
``children''. Professor Warwick (a roboticist from Reading University,
UK) thinks they may snatch the world from us before we are willing to
hand it over. Professor de Garis (head of the Artificial Brain Project
of Starlab, Belgium) thinks there will be a war between those who are
on the side of the robots and those who are against them. Kurzweil
(developer of some of the world's most advanced speech synthesisers
and recognisers) thinks that we can participate in this takeover by
superintelligences by having microscopic nanocomputers link themselves
into our brains and becoming superintelligent ourselves. What they
all do agree about is the inevitability of some kind of
superintelligent machine soon becoming vastly more intelligent than
us.

Like all the best conjuring tricks, the argument depends on
distracting you with astonishing facts while some assumptions sneak
past.

The astonishing facts are a generalisation of Moore's Law. In 1965
Gordon Moore, then of Fairchild (later to found Intel) predicted that
the amount of transistors packable into a silicon chip would double
every year. It turned out to be closer to 18 months. It affects both
computer processors and their associated on-board memory, i.e., the
two components most responsible for what we think of as ``computer
power''. In other words, we can expect computer power to double every
18 months. But for how long?

Computer scientists predict that the silicon chip technology on which
current computers are based has another ten to twenty years left
before it hits fundamental physical limits beyond which no further
progress in miniaturisation will be possible. What then? In fact, as
Moravec has shown, Moore's Law can be projected backwards since before
the dawn of ``silicon chips'', right back to the early pre-computer
clockwork calculators and tabulators. Moravec also normalises the
data to ``processing power per $1000 (1997)'' to produce a ``bang per
buck'' version of Moore's Law. When this data is plotted it can be
seen that Moore's Law has leapt seamlessly from technology to
technology, always finding a new one before the old one ran out of
steam. This suggests that Moore's Law is a specific example of some
deeper law concerning information processing technologies in general.
So, if this trend persists, we can expect Moore's Law to keep going,
leaping technologies again, and again, and again.

A robot of the 1950s (Grey Walter's Machina Speculatrix)

Forever? It turns out that we needn't worry about forever, because
something very interesting indeed happens in the next few
decades. Within a few decades $1000 (1997) will be able to buy a
computer with the processing power of the human brain, according to
our current best estimates of what that is. Such is the magic of this
kind of exponential growth of computer power (doubling every 18
months) that it doesn't matter if we have underestimated the power of
the human brain by a factor of 100. We would only have to wait another
ten years for these $1,000 computers to be 100 times more powerful.
Would you prefer to wait until the computers were as powerful as the
summed brain power of the entire planetary human population of six
billion people? You will just have to wait another 50 years.

In short, we have somehow managed to get ourselves onto a
technological escalator which will produce cheap computers of
superhuman processing power within a few to several decades. This is
the astonishing fact: computers are soon likely to outstrip the
processing power of the human brain.

The first assumption which sneaked past is that this increase in
computer processing power will automatically mean an increase
in the intelligence of whatever is using these computers for
brains. As Moravec has shown, this is what has happened so far in a
number of areas in robotics and AI. For example, the difference
between the very first autonomous robot ever made, Grey Walter's
Machina Speculatrix of the 1950s, and one of todays most
complex robots, Honda's P3, is very impressive indeed. In order for
machine intelligence to keep step with machine computer power,
however, we need a much stronger argument than that it often
happens. We need to be able to say that it always will, that
this is a general rule to which there are no exceptions.

A robot of the 2000s (Honda's P3)

Unfortunately there are exceptions. Artificial Intelligence (AI) has
achieved many successes with the kind of canned ``intelligence''
exemplified by Expert Systems which capture the expertise of a human
expert, often a consultant diagnostician such as a medical
specialist. These systems are, however, notoriously fragile, falling
apart quite idiotically when moved slightly beyond their area of
expertise. In other words, they lack the general underpinning of
``common sense'' which we have. They are also incapable of the widely
general, insightful, and rapid learning which characterises human
students. For example, if you can teach someone how to play chess, you
can also teach them how to play Mah Jong. But it is not possible to
adapt a chess-playing computer program to play Mah Jong, you have to
start all over again from scratch.

These two areas, of common sense and machine learning, are generally
recognised in AI (Artificial Intelligence) to be extremely difficult
research areas of which we are only just beginning to scratch the
surface. They are also generally recognised to be crucial to the
development of human-scale intelligence. The progress of AI in these
areas at the moment consists largely of finding out how very much more
complex they are than we first supposed.

The most important single lesson which AI has learned in its 50 years
of research is a generalisation of Hofstadter's Law of software
development: the problem is much more difficult than you think, even
when you take this into account. In other words, the optimists do not
have a good track record.

That is one reason why machine intelligence will not follow the
development of computational power.

Even if it did, however, that is still not enough to permit the
``robots will take over'' scenario, because the second assumption
which sneaked past is that something which displays some of the
attributes of creaturehood must possess all the attributes of
creaturehood. i.e., in effect be a real creature although built by
artificial means. We are strongly disposed by evolution and by habit
to suppose that anything displaying some aspects of animate
behaviour is animate. It's a usefully cautious assumption in a
dangerous world. The point about creatures is that millions of years
of evolution have equipped them with a fierce determination to
survive. This involves such things as attacking other creatures who
threaten their dinner or territory.

Intelligence is no more enough to make a real creature than is fur and
beady eyes. No matter how much intelligence is added to your word
processor it is not going to sulk and refuse to edit any more letters
if you don't improve your spelling. And no matter how much
intelligence you add to your washing machine, robot butler, or
whatever, it is not going to become anything more than a smarter
contraption. Our problem is that while we have got used to the idea
that teddy bears are not real even though we may be in the habit of
talking to them at length, we are not used to contraptions being
intelligent enough to talk back, and are willing to credit them with
possession of the full orchestra of creaturehood on hearing a few
flute-like notes.

MIT's Kismet ``emotional'' robot face

This is like what happened with Vaucanson's famous mechanical duck,
the duck which aroused such controversy that it still features today
in the saying ``if it walks like a duck, and quacks like a duck, then
it is a duck.'' In 1738 Vaucanson exhibited his marvelous mechanical
duck to an astonished Paris. It had multiply jointed realistic wings,
could move its head around and mimic the swallowing neck movements of
a duck, ``eat'' grain, splash water, etc.. The Parisians were used to
ingenious clockwork automata which played whistles, wrote with pen on
paper, etc., but what astounded them about this duck, and convinced
them that it was a real step forwards towards artificial life, was
that it had guts made of rubber hose and actually shat evil smelling
duck turds soon after eating. Unlike all the other ingenious clockwork
automata of the time, this one seemed to approach the miraculously
self-sustaining feature of life of (seeming to) get its energy from
grains instead of clockwork springs. Although it was fastened to a
large plinth full of the gears and pulleys that made it work, the
press of the day, being just as gullible as today's concerning these
matters, soon had it capable of walking and swimming and really
nourishing itself on grains. And of course, everyone started asking
``If this is what can be done now, what on earth will be
possible in another 50 years? If it walks like a duck, and quacks
like a duck, will it really be a duck?''

Joseph Weizenbaum was author of one of the early attempts at passing
the Turing Test for Artificial Intelligence, the well-known ``Eliza''
conversational program (some of its incarnations known as ``Doctor''
because it emulated the sympathetic enquiries of a
psychotherapist). In the 1970s he decided that he had seen so much
human gullibility and anthropomorphisation towards Eliza, some people
responding to ``her'' as though to a real person although ``she'' was
no more than a bag of barely plausible text manipulation tricks, that
he concluded that the human race was simply not intellectually mature
enough to meddle with such a seductive science as artificial
intelligence. We would simply make dreadful fools of ourselves by
anthropomorphising and over-interpreting everything. For example, it
is very difficult when faced with an apparently emotionally
responsive creature such as MIT's ``Kismet'' robot head not to imagine
it has real feelings behind those large eyes which follow you about,
blink, and frown.

I'm afraid that Messrs de Garis, Kurzweil, Moravec, Warwick, etc.,
have proved Weizenbaum all too prescient. I presume of course that the
fact that publishers and TV programme makers want to hear about robots
taking over, and don't want to hear about robots not taking over, has
nothing to do with it.